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Implementing keypoints_orb without using Harris response

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This commit is contained in:
Ankit Agrawal
2013-11-29 20:42:05 +01:00
committed by Johannes Schönberger
parent f9b6e1ba8f
commit 7d8c59135f
2 changed files with 37 additions and 1 deletions
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skimage/feature/__init__.py
+4 -1
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@@ -12,6 +12,7 @@ from .template import match_template
from ._brief import brief, match_keypoints_brief
from .util import pairwise_hamming_distance
from .censure import keypoints_censure
from .orb import keypoints_orb, descriptor_orb
__all__ = ['daisy',
'hog',
@@ -36,4 +37,6 @@ __all__ = ['daisy',
'structure_tensor',
'structure_tensor_eigvals',
'hessian_matrix',
'hessian_matrix_eigvals']
'hessian_matrix_eigvals',
'keypoints_orb',
'descriptor_orb']
skimage/feature/orb.py
+33
View File
@@ -3,6 +3,39 @@ import numpy as np
from ..util import img_as_float
from .util import _mask_border_keypoints
from skimage.feature import corner_fast, corner_orientations, corner_peaks
from skimage.transform import pyramid_gaussian
def keypoints_orb(image, n=9, threshold=0.20, downscale_factor=1.414,
n_scales=5):
image = np.squeeze(image)
if image.ndim != 2:
raise ValueError("Only 2-D gray-scale images supported.")
pyramid = list(pyramid_gaussian(image, n_scales - 1, downscale_factor))
ofast_mask = np.array([[0, 0, 1, 1, 1, 0, 0],
[0, 1, 1, 1, 1, 1, 0],
[1, 1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 1],
[0, 1, 1, 1, 1, 1, 0],
[0, 0, 1, 1, 1, 0, 0]], dtype=np.uint8)
keypoints = np.empty((0, 2), dtype=np.intp)
orientations = np.empty((0), dtype=np.double)
scales = np.empty((0), dtype=np.intp)
for i in range(n_scales):
corners = corner_peaks(corner_fast(pyramid[i], n, threshold), min_distance=1)
keypoints = np.vstack((keypoints, corners))
orientations = np.hstack((orientations, corner_orientations(pyramid[i], corners, ofast_mask)))
scales = np.hstack((scales, i * np.ones((corners.shape[0]), dtype=np.intp)))
return keypoints, orientations, scales
def descriptor_orb(image, keypoints, keypoints_angle):